This paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localization and tracking. The theory of graphical models is used to describe the statistical relationship between sensors, targets, and measurements. To jointly infer the states of sensors and targets, we use the statistical processing of belief propagation.

Joint Multitarget Tracking and Dynamic Network Localization in the Underwater Domain

Brambilla M.;Nicoli M.;
2020-01-01

Abstract

This paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localization and tracking. The theory of graphical models is used to describe the statistical relationship between sensors, targets, and measurements. To jointly infer the states of sensors and targets, we use the statistical processing of belief propagation.
2020
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
978-1-5090-6631-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1145015
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